Deep Learning: A Practitioner's Approach
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About this item
Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks.
Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J’s workflow tool Learn how to use DL4J natively on Spark and Hadoop
ASIN: 1491914254
VSKU: 4EKGU900EBOF_ns
Condition: Acceptable
Author/Artist:Patterson, Josh|Gibson, Adam
Binding: Paperback
Note: Any images shown are stock photographs and product may differ from what is shown.
Condition Notes: This copy has clearly been enjoyed—expect noticeable shelf wear and some minor creases to the cover. Binding is strong, and all pages are legible. May contain previous library markings or stamps.
ASIN: 1491914254
VSKU: 4EKGU900EBOF_ns
Condition: Acceptable
Author/Artist:Patterson, Josh|Gibson, Adam
Binding: Paperback
Note: Any images shown are stock photographs and product may differ from what is shown.
Condition Notes: This copy has clearly been enjoyed—expect noticeable shelf wear and some minor creases to the cover. Binding is strong, and all pages are legible. May contain previous library markings or stamps.
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